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Location
UM Bannatyne: Brodie Centre: Room-405
Address:
Description:
This 5-day hands-on and in-person workshop presented by the George & Fay Yee Centre for Healthcare Innovation (CHI) will introduce participants to machine learning with Python through a combination of instruction and hands-on exercises. Participants will develop intuition into the inner workings of various machine learning models, including tree-based models and artificial neural networks. The workshop emphasizes practical applications, equipping participants with skills to develop and evaluate machine learning models for the health sciences.
Previous experience with Python programming is required to register for this workshop. Please register for our Python Essentials for Data Science workshop prior to attending Fundamentals of Machine Learning or contact us to confirm if you have the necessary background. Participants will be expected to bring a Windows or Apple laptop and must have a Google account to access the Google Colab cloud computing environment. Instructions for setting up Google Colab will be provided upon registration.
Sessions will be held from 9am to 12pm (CT) on October 28th, 30th ; November 1st, 5th, and 7th.
Location: Brodie Centre: Room-405
Learning objectives:
- Develop a deeper understanding of machine learning workflows from data preparation to model inference
- Understand and apply different machine learning paradigms, including unsupervised clustering, and supervised regression and classification (binary and multi-class)
- Deepen your understanding of tree-based models including decision trees, random forests, and gradient boosting machines (e.g., XGBoost)
- Explore the fundamentals of deep learning with artificial neural networks
- Address common machine learning challenges such as overfitting, class imbalance, and gradient issues
- Enhance model performance through ensemble learning
- Gain practical skills working with common Python machine learning libraries, including scikit-learn and PyTorch
Cost:
$50.00 – Academic trainees and students (post-docs included), $150.00 – Non-profit organizations staff, $300.00 – Industry professionals
Contact Information:
For more information, please contact Barret Monchka.
Registration Cancellation Policy:
A registration refund will be made upon written request on or before October 21st, 2024. A $35 administrative fee will be retained. No refunds will be made for cancellations after this date.
